This episode explores data poisoning and its growing impact on AI systems, from model backdoors to agent memory risk. Ioana and Chris chat with Microsoft's Giorgio Severi about how adversaries manipulate data, why these attacks are hard to detect, and what it takes to build layered defenses that keep AI systems reliable, safe, and trustworthy.

What You Will Learn:

• Understand what AI red teaming is and why it’s critical for safe AI deployment
• Learn how data and model poisoning can subtly influence AI behavior over time
• Explore why AI systems can fail silently (e.g., backdoors and hidden triggers)
• Discover the importance of layered security (“defense in depth”) in AI systems
• Gain insight into new risks in AI agents, especially around memory and persistence
• Get practical guidance on how to design and test more trustworthy AI systems

Publications:
[2602.03085] The Trigger in the Haystack: Extracting and Reconstructing LLM Backdoor Triggers
[1708.06733] BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

#EnterpriseAI #AISafety #TrustworthyAI #AIGovernance #AgenticAI #AIResearch